1. Choose the starting point
Bring a recurring engineering task or a clearly bounded pilot case.
Product
AI Agent
4 modes, 19+ tools, extended thinking
Code Review
Automated reviews with HTML/JSON export
Security Scanning
4 scan skills, SARIF, inline diagnostics
Multi-Agent
Autonomous planning with quality gates
Team management
Wallet, budgets, and admin policies
Git & GitHub
Automated commits, PRs, and issues
Testing & TDD
Test generation and TDD workflows
Documentation
Auto-docs, Mermaid, Changelog
IDE & CLI
Extensions
Skills
Community skills and custom commands
MCP Integration
Model Context Protocol servers
Custom Agents & Rules
Custom agents, rules, LURUS.md
Code Indexing
Semantic search with RAG
Hooks
Event automation with 11 events
Web Search & Browser
Brave Search, browser automation
Permissions
Sandbox isolation, file guards, command allowlists
API Keys
Token-based auth for CI/CD and headless environments
Security
GDPR & Data Protection
Your code is never stored. GDPR-compliant processing with immediate data deletion.
View our security standardsDemo
Frame a concrete engineering workflow together
A useful demo starts with a real task: a repository, a quality goal, or a decision about model and provider routes.
Demo
2. Walk through the workflow
See how planning, implementation, tests, and reviews can work together in an agentic flow.
3. Frame the data path
Review the model, provider, and processing region; Zero Data Retention and no training on customer data apply by default.
4. Decide the next step
Decide whether a limited pilot, further review, or another path makes sense.
Helpful preparation for a meaningful demo
- A typical task or representative pull request
- Your existing test, review, and deployment gates
- Questions about model, provider, region, or internal usage policies